Various on-line services permit submission of content from the public or at least from registered users. For example, photo and video sharing sites let users upload digital images and videos that they have taken, respectively. On-line classified sites allow users to upload advertisements for goods or services that they may be offering for sale to other users. Job sites may allow employers to post job listing, and prospective employees to post resumes. Other forms of sites may also be provided in appropriate circumstances.
Because such sites accept content from the general public, the services they offer may from time-to-time be abused. For example, photos containing objectionable images may be uploaded by a user. Or a post may include inappropriate language, or be directed inappropriately at another user. Other submissions may violate a terms of service agreement with the service provider in other manners. Even when the content is appropriate, systems may allow users to rate the content (e.g., on a scale of zero to five stars).
As a result, such service providers frequently provide mechanisms by which the public that views the posts can report inappropriate content or can rate the content—known as “negative feedback” systems. However, the people who report abuse may themselves be illegitimate, in that they may be objecting to an appropriate post from someone they do not like. Or, they may be marking posts as inappropriate simply out of general spite. Such malicious reports may be particularly harmful, because one does not expect the “crowd” to provide as much negative feedback as it might provide in a positive feedback system (e.g., with a 5-star rating system), and thus each report will have more influence. Malicious users may also mark a large number of posts in order to harm the reputation of the service itself, and they may work in large groups (either through many users entering manual reports, or many computers working automatically, such as under the control of a bot net) in order to overload a service provider—either in terms of an ability to provide sufficient bandwidth, or in an ability to review abuse reports so as to distinguish legitimate reports from illegitimate reports. At the same time, incorrect reports might occur innocently, as by a user accidentally clicking on a web page button, or the user not fully understanding a site's terms of service. Such users should not have their reputations harmed by infrequent mistakes.
Such negative feedback postings can be reviewed by human representatives with the assistance of automated tools, in an attempt to isolate legitimate posters from illegitimate posters, and to remove from the system bad content. However, resources for conducting such a manual review are limited, and the content systems can be extremely large and have many postings. Thus, manual review of postings should be conducted judiciously. In considering such a problem, consider the following puzzle. Alice flips a coin repeatedly and calls out the outcome without showing Bob the outcome. Alice may lie. Bob either accepts the outcome, or calls for a “check”, where the true outcome of the coin flip is revealed, and Bob will catch it if Alice had lied. Now, Bob can accept all outcomes without checking and may be erroneous if Alice lied without bounds, or at the other extreme, Bob may check Alice's every call and be sure of all outcomes. But that will waste a lot of effort for Bob that could better be spent elsewhere. A goal is to achieve acceptable accuracy in the review of negative feedback, with acceptable cost of performing the review.